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05/19/2022
Augmented Lagrangian Methods for Time-varying Constrained Online Convex Optimization
In this paper, we consider online convex optimization (OCO) with time-va...
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11/03/2021
Convergent and orthogonality preserving schemes for approximating the Kohn-Sham orbitals
To obtain convergent numerical approximations without using any orthogon...
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06/22/2021
A stochastic linearized proximal method of multipliers for convex stochastic optimization with expectation constraints
This paper considers the problem of minimizing a convex expectation func...
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11/16/2018
Synergistic Drug Combination Prediction by Integrating Multi-omics Data in Deep Learning Models
Drug resistance is still a major challenge in cancer therapy. Drug combi...
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02/24/2018
Kernel-smoothed proper orthogonal decomposition (KSPOD)-based emulation for prediction of spatiotemporally evolving flow dynamics
This interdisciplinary study, which combines machine learning, statistic...
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07/26/2017